Bluetooth enhancements (service data inspector, appearance codes, MAC
cluster tracking, behavioral flags, IRK badges, distance estimation),
ACARS SoapySDR multi-backend support, dump1090 stale process cleanup,
GPS error state, and proximity radar/signal card UI improvements.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
New Features:
- Meshtastic LoRa mesh network integration
- Real-time message streaming via SSE
- Channel configuration with encryption
- Node information with RSSI/SNR metrics
- Ubertooth One BLE scanner backend
- Passive capture across all 40 BLE channels
- Raw advertising payload access
- Offline mode with bundled assets
- Local Leaflet, Chart.js, and fonts
- Multiple map tile providers
- Settings modal for configuration
Technical Changes:
- New routes: meshtastic.py, offline.py
- New utils: ubertooth_scanner.py, meshtastic.py
- New CSS/JS for meshtastic and settings
- Updated dashboard templates with conditional asset loading
- Added context processor for offline settings
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implement reliable tracker detection for AirTag, Tile, Samsung SmartTag,
and other BLE trackers based on manufacturer data patterns, service UUIDs,
and advertising payload analysis.
Key changes:
- Add TrackerSignatureEngine with signatures for major tracker brands
- Device fingerprinting to track devices across MAC randomization
- Suspicious presence heuristics (persistence, following patterns)
- New API endpoints: /api/bluetooth/trackers, /diagnostics
- UI updates with tracker badges, confidence, and evidence display
- TSCM integration updated to use v2 tracker detection data
- Unit tests and smoke test scripts for validation
Detection is heuristic-based with confidence scoring (high/medium/low)
and evidence transparency. Backwards compatible with existing APIs.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Backend:
- Add device_key.py for stable device identification (identity > public MAC > fingerprint)
- Add distance.py with DistanceEstimator class (path-loss formula, EMA smoothing, confidence scoring)
- Add ring_buffer.py for time-windowed RSSI observation storage
- Extend BTDeviceAggregate with proximity_band, estimated_distance_m, distance_confidence, rssi_ema
- Add new API endpoints: /proximity/snapshot, /heatmap/data, /devices/<key>/timeseries
- Update TSCM integration to include new proximity fields
Frontend:
- Add proximity-radar.js: SVG radar with concentric rings, device dots positioned by distance
- Add timeline-heatmap.js: RSSI history grid with time buckets and color-coded signal strength
- Update bluetooth.js to initialize and feed data to new components
- Replace zone counters with radar visualization and zone summary
- Add proximity-viz.css for component styling
Tests:
- Add test_bluetooth_proximity.py with unit tests for device key stability, EMA smoothing,
distance estimation, band classification, and ring buffer functionality
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add 'available' alias for 'can_scan' in capabilities
- Add 'preferred_backend' alias for 'recommended_backend'
- Add 'id' field to adapter info for frontend compatibility
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Major changes:
- Add utils/bluetooth/ package with DBus scanner, fallback scanners
(bleak, hcitool, bluetoothctl), device aggregation, and heuristics
- New unified API at /api/bluetooth/ with REST endpoints and SSE streaming
- Device observation aggregation with RSSI statistics and range bands
- Behavioral heuristics: new, persistent, beacon-like, strong+stable
- Frontend components: DeviceCard, MessageCard, RSSISparkline
- TSCM integration via get_tscm_bluetooth_snapshot() helper
- Unit tests for aggregator, heuristics, and API endpoints
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
